code: def resnet152(pretrained=False, **kwargs):
      """Constructs a ResNet-152 model.
  
      Args:
          pretrained (bool): If True, returns a model pre-trained on ImageNet
      """
      model = ResNet(Bottleneck, [3, 8, 36, 3], **kwargs)
      if pretrained:
          model.load_state_dict(
              model_zoo.load_url(model_urls["resnet152"])
          )
      return model
  
imports: from __future__ import print_function, division, absolute_import
  import torch.nn
  import math
  import torch.utils.model_zoo
  from torch.legacy import nn
  import torchfile
  from torch.utils.serialization import load_lua
  import torch
  import collections
  from PIL import Image
  import torchvision.transforms
label_desc: Use image node_id 6 for calling a global function with example usage: resnet152(pretrained) and returns: model